In vivo neutralization of coral snake venoms with an oligoclonal nanobody mixture in a murine challenge model.

Oligoclonal mixtures of broadly-neutralizing antibodies can neutralize complex compositions of similar and dissimilar antigens, making them versatile tools for the treatment of e.g., infectious diseases and animal envenomations. However, these biotherapeutics are complicated to develop due to their complex nature. In this work, we describe the application of various strategies for the discovery of cross-neutralizing nanobodies against key toxins in coral snake venoms using phage display technology. We prepare two oligoclonal mixtures of nanobodies and demonstrate their ability to neutralize the lethality induced by two North American coral snake venoms in mice, while individual nanobodies fail to do so. We thus show that an oligoclonal mixture of nanobodies can neutralize the lethality of venoms where the clinical syndrome is caused by more than one toxin family in a murine challenge model. The approaches described may find utility for the development of advanced biotherapeutics against snakebite envenomation and other pathologies where multi-epitope targeting is beneficial.

Glycoengineered recombinant alpha1-antitrypsin results in comparable in vitro and in vivo activities to human plasma-derived protein.

Alpha-1-antitrypsin (A1AT) is a multifunctional, clinically important, high value therapeutic glycoprotein that can be used for the treatment of many diseases such as alpha-1-antitrypsin deficiency, diabetes, graft-versus-host-disease, cystic fibrosis and various viral infections. Currently, the only FDA-approved treatment for A1AT disorders is intravenous augmentation therapy with human plasma-derived A1AT. In addition to its limited supply, this approach poses a risk of infection transmission, since it uses therapeutic A1AT harvested from donors. To address these issues, we sought to generate recombinant human A1AT (rhA1AT) that is chemically and biologically indistinguishable from its plasma-derived counterpart using glycoengineered Chinese Hamster Ovary (geCHO-L) cells. By deleting nine key genes that are part of the CHO glycosylation machinery and expressing the human ST6GAL1 and A1AT genes, we obtained stable, high producing geCHO-L lines that produced rhA1AT having an identical glycoprofile to plasma-derived A1AT (pdA1AT). Additionally, the rhA1AT demonstrated in vitro activity and in vivo half-life comparable to commercial pdA1AT. Thus, we anticipate that this platform will help produce human-like recombinant plasma proteins, thereby providing a more sustainable and reliable source of therapeutics that are cost-effective and better-controlled with regard to purity, clinical safety and quality.

LeGenD: determining N-glycoprofiles using an explainable AI-leveraged model with lectin profiling.

Glycosylation affects many vital functions of organisms. Therefore, its surveillance is critical from basic science to biotechnology, including biopharmaceutical development and clinical diagnostics. However, conventional glycan structure analysis faces challenges with throughput and cost. Lectins offer an alternative approach for analyzing glycans, but they only provide glycan epitopes and not full glycan structure information. To overcome these limitations, we developed LeGenD, a lectin and AI-based approach to predict N-glycan structures and determine their relative abundance in purified proteins based on lectin-binding patterns. We trained the LeGenD model using 309 glycoprofiles from 10 recombinant proteins, produced in 30 glycoengineered CHO cell lines. Our approach accurately reconstructed experimentally-measured N-glycoprofiles of bovine Fetuin B and IgG from human sera. Explanatory AI analysis with SHapley Additive exPlanations (SHAP) helped identify the critical lectins for glycoprofile predictions. Our LeGenD approach thus presents an alternative approach for N-glycan analysis.

Antibody-dependent enhancement of toxicity of myotoxin II from Bothrops asper.

Improved therapies are needed against snakebite envenoming, which kills and permanently disables thousands of people each year. Recently developed neutralizing monoclonal antibodies against several snake toxins have shown promise in preclinical rodent models. Here, we use phage display technology to discover a human monoclonal antibody and show that this antibody causes antibody-dependent enhancement of toxicity (ADET) of myotoxin II from the venomous pit viper, Bothrops asper, in a mouse model of envenoming that mimics a snakebite. While clinical ADET related to snake venom has not yet been reported in humans, this report of ADET of a toxin from the animal kingdom highlights the necessity of assessing even well-known antibody formats in representative preclinical models to evaluate their therapeutic utility against toxins or venoms. This is essential to avoid potential deleterious effects as exemplified in the present study.

Inferring secretory and metabolic pathway activity from omic data with secCellFie.

Understanding protein secretion has considerable importance in biotechnology and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer properties of protein secretion from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can help predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells.

Phage display assisted discovery of a pH-dependent anti-α-cobratoxin antibody from a natural variable domain library.

Recycling IgG antibodies bind to their target antigen at physiological pH in the blood stream and release them upon endocytosis when pH levels drop, allowing the IgG antibodies to be recycled into circulation via FcRn-mediated cellular pathways, while the antigens undergo lysosomal degradation. This enables recycling antibodies to achieve comparable therapeutic effect at lower doses than their non-recycling counterparts. The development of such antibodies is typically achieved by histidine doping of their variable regions or by performing in vitro antibody selection campaigns utilizing histidine doped libraries. Both are strategies that may introduce sequence liabilities. Here, we present a methodology that employs a naïve antibody phage display library, consisting of natural variable domains, to discover antibodies that bind α-cobratoxin from the venom of Naja kaouthia in a pH-dependent manner. As a result, an antibody was discovered that exhibits a 7-fold higher off-rate at pH 5.5 than pH 7.4 in bio-layer interferometry experiments. Interestingly, no histidine residues were found in its variable domains, and in addition, the antibody showed pH-dependent binding to a histidine-devoid antigen mutant. As such, the results demonstrate that pH-dependent antigen-antibody binding may not always be driven by histidine residues. By employing molecular dynamics simulations, different protonation states of titratable residues were found, which potentially could be responsible for the observed pH-dependent antigen binding properties of the antibody. Finally, given the typically high diversity of naïve antibody libraries, the methodology presented here can likely be applied to discover recycling antibodies against different targets ab initio without the need for histidine doping.

Discovery of a human monoclonal antibody that cross-neutralizes venom phospholipase A2s from three different snake genera.

Despite the considerable global impact of snakebite envenoming, available treatments remain suboptimal. Here, we report the discovery of a broadly-neutralizing human monoclonal antibody, using a phage display-based cross-panning strategy, capable of reducing the cytotoxic effects of venom phospholipase A2s from three different snake genera from different continents. This highlights the potential of utilizing monoclonal antibodies to develop more effective, safer, and globally accessible polyvalent antivenoms that can be widely used to treat snakebite envenoming.

Characterisation of two snake toxin-targeting human monoclonal immunoglobulin G antibodies expressed in tobacco plants.

Current snakebite antivenoms are based on polyclonal animal-derived antibodies, which can neutralize snake venom toxins in envenomed victims, but which are also associated with adverse reactions. Therefore, several efforts within antivenom research aim to explore the utility of recombinant monoclonal antibodies, such as human immunoglobulin G (IgG) antibodies, which are routinely used in the clinic for other indications. In this study, the feasibility of using tobacco plants as bioreactors for expressing full-length human monoclonal IgG antibodies against snake toxins was investigated. We show that the plant-produced antibodies perform similarly to their mammalian cell-expressed equivalents in terms of in vitro antigen binding. Complete neutralization was achieved by both the plant and mammalian cell-produced anti-α-cobratoxin antibody. The feasibility of using plant-based expression systems may potentially make it easier for laboratories in resource-poor settings to work with human monoclonal IgG antibodies.

Inferring secretory and metabolic pathway activity from omic data with secCellFie.

Understanding protein secretion has considerable importance in the biotechnology industry and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer protein secretion capabilities from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can be used to predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells.

Assessing developability early in the discovery process for novel biologics.

Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

Discovery and optimization of a broadly-neutralizing human monoclonal antibody against long-chain α-neurotoxins from snakes.

Snakebite envenoming continues to claim many lives across the globe, necessitating the development of improved therapies. To this end, broadly-neutralizing human monoclonal antibodies may possess advantages over current plasma-derived antivenoms by offering superior safety and high neutralization capacity. Here, we report the establishment of a pipeline based on phage display technology for the discovery and optimization of high affinity broadly-neutralizing human monoclonal antibodies. This approach yielded a recombinant human antibody with superior broadly-neutralizing capacities in vitro and in vivo against different long-chain α-neurotoxins from elapid snakes. This antibody prevents lethality induced by Naja kaouthia whole venom at an unprecedented low molar ratio of one antibody per toxin and prolongs the survival of mice injected with Dendroaspis polylepis or Ophiophagus hannah whole venoms.

CHOGlycoNET: Comprehensive glycosylation reaction network for CHO cells.

Chinese hamster ovary (CHO) cells are extensively used for the production of glycoprotein therapeutics proteins, for which N-linked glycans are a critical quality attribute due to their influence on activity and immunogenicity. Manipulation of protein glycosylation is commonly achieved through cell or process engineering, which are often guided by mathematical models. However, each study considers a unique glycosylation reaction network that is tailored around the cell line and product at hand. Herein, we use 200 glycan datasets for both recombinantly produced and native proteins from different CHO cell lines to reconstruct a comprehensive reaction network, CHOGlycoNET, based on the individual minimal reaction networks describing each dataset. CHOGlycoNET is used to investigate the distribution of mannosidase and glycosyltransferase enzymes in the Golgi apparatus and identify key network reactions using machine learning and dimensionality reduction techniques. CHOGlycoNET can be used for accelerating glycomodel development and predicting the effect of glycoengineering strategies. Finally, CHOGlycoNET is wrapped in a SBML file to be used as a standalone model or in combination with CHO cell genome scale models.

Highly Selective Lysine Acylation in Proteins Using a Lys-His Tag Sequence.

Chemical modification of proteins has numerous applications, but it has been challenging to achieve the required high degree of selectivity on lysine amino groups. Recently, we described the highly selective acylation of proteins with an N-terminal Gly-His6 segment. This tag promoted acylation of the N-terminal Nα -amine resulting in stable conjugates. Herein, we report the peptide sequences Hisn -Lys-Hism , which we term Lys-His tags. In combination with simple acylating agents, they facilitate the acylation of the designated Lys Nϵ -amine under mild conditions and with high selectivity over native Lys residues. We show that the Lys-His tags, which are 7 to 10 amino acids in length and still act as conventional His tags, can be inserted in proteins at the C-terminus or in loops, thus providing high flexibility regarding the site of modification. Finally, the selective and efficient acylation of the therapeutic antibody Rituximab, pure or mixed with other proteins, demonstrates the scope of the Lys-His tag acylation method.

Compartmentalized Proteomic Profiling Outlines the Crucial Role of the Classical Secretory Pathway during Recombinant Protein Production in Chinese Hamster Ovary Cells.

Different cellular processes that contribute to protein production in Chinese hamster ovary (CHO) cells have been previously investigated by proteomics. However, although the classical secretory pathway (CSP) has been well documented as a bottleneck during recombinant protein (RP) production, it has not been well represented in previous proteomic studies. Hence, the significance of this pathway for production of RP was assessed by identifying its own proteins that were associated to changes in RP production, through subcellular fractionation coupled to shot-gun proteomics. Two CHO cell lines producing a monoclonal antibody with different specific productivities were used as cellular models, from which 4952 protein groups were identified, which represent a coverage of 59% of the Chinese hamster proteome. Data are available via ProteomeXchange with identifier PXD021014. By using SAM and ROTS algorithms, 493 proteins were classified as differentially expressed, of which about 80% was proposed as novel targets and one-third were assigned to the CSP. Endoplasmic reticulum (ER) stress, unfolded protein response, calcium homeostasis, vesicle traffic, glycosylation, autophagy, proteasomal activity, protein synthesis and translocation into ER lumen, and secretion of extracellular matrix components were some of the affected processes that occurred in the secretory pathway. Processes from other cellular compartments, such as DNA replication, transcription, cytoskeleton organization, signaling, and metabolism, were also modified. This study gives new insights into the molecular traits of higher producer cells and provides novel targets for development of new sub-lines with improved phenotypes for RP production.

In situ detection of protein interactions for recombinant therapeutic enzymes.

Despite their therapeutic potential, many protein drugs remain inaccessible to patients since they are difficult to secrete. Each recombinant protein has unique physicochemical properties and requires different machinery for proper folding, assembly, and posttranslational modifications (PTMs). Here we aimed to identify the machinery supporting recombinant protein secretion by measuring the protein-protein interaction (PPI) networks of four different recombinant proteins (SERPINA1, SERPINC1, SERPING1, and SeAP) with various PTMs and structural motifs using the proximity-dependent biotin identification (BioID) method. We identified PPIs associated with specific features of the secreted proteins using a Bayesian statistical model and found proteins involved in protein folding, disulfide bond formation, and N-glycosylation were positively correlated with the corresponding features of the four model proteins. Among others, oxidative folding enzymes showed the strongest association with disulfide bond formation, supporting their critical roles in proper folding and maintaining the ER stability. Knockdown of disulfide-isomerase PDIA4, a measured interactor with significance for SERPINC1 but not SERPINA1, led to the decreased secretion of SERPINC1, which relies on its extensive disulfide bonds, compared to SERPINA1, which has no disulfide bonds. Proximity-dependent labeling successfully identified the transient interactions supporting synthesis of secreted recombinant proteins and refined our understanding of key molecular mechanisms of the secretory pathway during recombinant protein production.

CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines.

Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While high-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multi-layer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to accommodate other types of omics data and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research.

Independent component analysis of E. coli's transcriptome reveals the cellular processes that respond to heterologous gene expression.

Achieving the predictable expression of heterologous genes in a production host has proven difficult. Each heterologous gene expressed in the same host seems to elicit a different host response governed by unknown mechanisms. Historically, most studies have approached this challenge by manipulating the properties of the heterologous gene through methods like codon optimization. Here we approach this challenge from the host side. We express a set of 45 heterologous genes in the same Escherichia coli strain, using the same expression system and culture conditions. We collect a comprehensive RNAseq set to characterize the host's transcriptional response. Independent Component Analysis of the RNAseq data set reveals independently modulated gene sets (iModulons) that characterize the host response to heterologous gene expression. We relate 55% of variation of the host response to: Fear vs Greed (16.5%), Metal Homeostasis (19.0%), Respiration (6.0%), Protein folding (4.5%), and Amino acid and nucleotide biosynthesis (9.0%). If these responses can be controlled, then the success rate with predicting heterologous gene expression should increase.

High throughput generation of a resource of the human secretome in mammalian cells.

The proteins secreted by human tissues and blood cells, the secretome, are important both for the basic understanding of human biology and for identification of potential targets for future diagnosis and therapy. Here, a high-throughput mammalian cell factory is presented that was established to create a resource of recombinant full-length proteins covering the majority of those annotated as 'secreted' in humans. The full-length DNA sequences of each of the predicted secreted proteins were generated by gene synthesis, the constructs were transfected into Chinese hamster ovary (CHO) cells and the recombinant proteins were produced, purified and analyzed. Almost 1,300 proteins were successfully generated and proteins predicted to be secreted into the blood were produced with a success rate of 65%, while the success rates for the other categories of secreted proteins were somewhat lower giving an overall one-pass success rate of ca. 58%. The proteins were used to generate targeted proteomics assays and several of the proteins were shown to be active in a phenotypic assay involving pancreatic ß-cell dedifferentiation. Many of the proteins that failed during production in CHO cells could be rescued in human embryonic kidney (HEK 293) cells suggesting that a cell factory of human origin can be an attractive alternative for production in mammalian cells. In conclusion, a high-throughput protein production and purification system has been successfully established to create a unique resource of the human secretome.

A Markov model of glycosylation elucidates isozyme specificity and glycosyltransferase interactions for glycoengineering.

Glycosylated biopharmaceuticals are important in the global pharmaceutical market. Despite the importance of their glycan structures, our limited knowledge of the glycosylation machinery still hinders controllability of this critical quality attribute. To facilitate discovery of glycosyltransferase specificity and predict glycoengineering efforts, here we extend the approach to model N-linked protein glycosylation as a Markov process. Our model leverages putative glycosyltransferase (GT) specificity to define the biosynthetic pathways for all measured glycans, and the Markov chain modelling is used to learn glycosyltransferase isoform activities and predict glycosylation following glycosyltransferase knock-in/knockout. We apply our methodology to four different glycoengineered therapeutics (i.e., Rituximab, erythropoietin, Enbrel, and alpha-1 antitrypsin) produced in CHO cells. Our model accurately predicted N-linked glycosylation following glycoengineering and further quantified the impact of glycosyltransferase mutations on reactions catalyzed by other glycosyltransferases. By applying these learned GT-GT interaction rules identified from single glycosyltransferase mutants, our model further predicts the outcome of multi-gene glycosyltransferase mutations on the diverse biotherapeutics. Thus, this modeling approach enables rational glycoengineering and the elucidation of relationships between glycosyltransferases, thereby facilitating biopharmaceutical research and aiding the broader study of glycosylation to elucidate the genetic basis of complex changes in glycosylation.

Multiplex secretome engineering enhances recombinant protein production and purity.

Host cell proteins (HCPs) are process-related impurities generated during biotherapeutic protein production. HCPs can be problematic if they pose a significant metabolic demand, degrade product quality, or contaminate the final product. Here, we present an effort to create a "clean" Chinese hamster ovary (CHO) cell by disrupting multiple genes to eliminate HCPs. Using a model of CHO cell protein secretion, we predict that the elimination of unnecessary HCPs could have a non-negligible impact on protein production. We analyze the HCP content of 6-protein, 11-protein, and 14-protein knockout clones. These cell lines exhibit a substantial reduction in total HCP content (40%-70%). We also observe higher productivity and improved growth characteristics in specific clones. The reduced HCP content facilitates purification of a monoclonal antibody. Thus, substantial improvements can be made in protein titer and purity through large-scale HCP deletion, providing an avenue to increased quality and affordability of high-value biopharmaceuticals.